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33 Publications
2025 | Conference Paper | LibreCat-ID: 56298 | 
Gerlach, Raphael, et al. “Symmetry Preservation in Swarms of Oblivious Robots with Limited Visibility.” 28th International Conference on Principles of Distributed Systems (OPODIS 2024), edited by Silvia Bonomi et al., vol. 324, Schloss Dagstuhl -- Leibniz-Zentrum für Informatik, 2025, doi:10.4230/LIPIcs.OPODIS.2024.13.
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| arXiv
2024 | Journal Article | LibreCat-ID: 54548
Prager, Raphael Patrick, and Heike Trautmann. “Exploratory Landscape Analysis for Mixed-Variable Problems.” IEEE Transactions on Evolutionary Computation, 2024, pp. 1–1, doi:10.1109/TEVC.2024.3399560.
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2023 | Conference Paper | LibreCat-ID: 37312 |
Leffrang, Dirk, et al. “Do People Recover from Algorithm Aversion? An Experimental Study of Algorithm Aversion over Time.” Hawaii International Conference on System Sciences, 2023.
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2023 | Conference Paper | LibreCat-ID: 50121
Leffrang, Dirk. “AI Washing: The Framing Effect of Labels on Algorithmic Advice Utilization.” International Conference on Information Systems, no. 10, 2023.
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2023 | Conference Paper | LibreCat-ID: 50118
Leffrang, Dirk. “The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization.” Wirtschaftsinformatik Conference, no. 19, 2023.
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2023 | Journal Article | LibreCat-ID: 46310
Heins, Jonathan, et al. “A Study on the Effects of Normalized TSP Features for Automated Algorithm Selection.” Theoretical Computer Science, vol. 940, 2023, pp. 123–45, doi:https://doi.org/10.1016/j.tcs.2022.10.019.
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2023 | Book Chapter | LibreCat-ID: 54428
Schulte Eickholt, Swen. “Normative Diversität? Nahe Zukunft bei Sibylle Berg und Marc-Uwe Kling.” Germanistik im Wandel 1. Neue Einsichten und Perspektiven in der Literaturwissenschaft, edited by Leyla Cosan et al., Logos, 2023, pp. 65–75.
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2021 | Book Chapter | LibreCat-ID: 48881
Heins, Jonathan, et al. “On the Potential of Normalized TSP Features for Automated Algorithm Selection.” Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, 2021, pp. 1–15.
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2020 | Conference Paper | LibreCat-ID: 48897
Seiler, Moritz, et al. “Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem.” Parallel Problem Solving from {Nature} (PPSN XVI), Springer-Verlag, 2020, pp. 48–64, doi:10.1007/978-3-030-58112-1_4.
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2020 | Journal Article | LibreCat-ID: 48848
Bossek, Jakob, et al. “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms.” Applied Soft Computing, vol. 88, no. C, 2020, doi:10.1016/j.asoc.2019.105901.
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2020 | Journal Article | LibreCat-ID: 46334
Bossek, Jakob, et al. “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms.” Applied Soft Computing, vol. 88, 2020, p. 105901, doi:https://doi.org/10.1016/j.asoc.2019.105901.
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2019 | Journal Article | LibreCat-ID: 6512 |
Rauchecker, Gerhard, and Guido Schryen. “Using High Performance Computing for Unrelated Parallel Machine Scheduling with Sequence-Dependent Setup Times: Development and Computational Evaluation of a Parallel Branch-and-Price Algorithm.” Computers & Operations Research, no. 104, Elsevier, 2019, pp. 338–57.
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2019 | Conference Paper | LibreCat-ID: 48875
Bossek, Jakob, and Heike Trautmann. “Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time.” Learning and Intelligent Optimization, edited by Roberto Battiti et al., Springer International Publishing, 2019, pp. 215–219, doi:10.1007/978-3-030-05348-2_19.
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2018 | Conference Paper | LibreCat-ID: 3422
Robinson, Peter, et al. “Breaking the $\tilde\Omega(\sqrt{n})$ Barrier: Fast Consensus under a Late Adversary.” Proceedings of the 30th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), doi:10.1145/3210377.3210399.
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2018 | Conference Paper | LibreCat-ID: 48885
Kerschke, Pascal, et al. “Parameterization of State-of-the-Art Performance Indicators: A Robustness Study Based on Inexact TSP Solvers.” Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, 2018, pp. 1737–1744, doi:10.1145/3205651.3208233.
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2018 | Journal Article | LibreCat-ID: 48884
Kerschke, Pascal, et al. “Leveraging TSP Solver Complementarity through Machine Learning.” Evolutionary Computation, vol. 26, no. 4, 2018, pp. 597–620, doi:10.1162/evco_a_00215.
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2018 | Conference Paper | LibreCat-ID: 1590
Lass, Michael, et al. “A Massively Parallel Algorithm for the Approximate Calculation of Inverse P-Th Roots of Large Sparse Matrices.” Proc. Platform for Advanced Scientific Computing (PASC) Conference, ACM, 2018, doi:10.1145/3218176.3218231.
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| arXiv
2017 | Conference Paper | LibreCat-ID: 17652
Polevoy, Gleb, et al. “Filtering Undesirable Flows in Networks.” Combinatorial Optimization and Applications: 11th International Conference, COCOA 2017, Shanghai, China, December 16-18, 2017, Proceedings, Part I, Springer International Publishing, 2017, pp. 3–17, doi:10.1007/978-3-319-71150-8_1.
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2016 | Conference Paper | LibreCat-ID: 48873
Bossek, Jakob, and Heike Trautmann. “Evolving Instances for Maximizing Performance Differences of State-of-the-Art Inexact TSP Solvers.” Learning and Intelligent Optimization, edited by Paola Festa et al., Springer International Publishing, 2016, pp. 48–59, doi:10.1007/978-3-319-50349-3_4.
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2014 | Conference Paper | LibreCat-ID: 9879
Kimotho, James Kuria, et al. “PEM Fuel Cell Prognostics Using Particle Filter with Model Parameter Adaptation.” Prognostics and Health Management (PHM), 2014 IEEE Conference On, 2014, pp. 1–6, doi:10.1109/ICPHM.2014.7036406.
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